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 SM ISO690:2012ZAPOROJAN, Sergiu, CĂRBUNE, Viorel, CALMÎCOV, Igor. Data-Based Technique for Extracting Knowledge from Data Generated in Experiments. In: IEEE International Conference on Intelligent Computer Communication and Processing: ICCP 2020, 3-5 septembrie 2020, Cluj-Napoca. New Jersey, SUA: Institute of Electrical and Electronics Engineers Inc., 2020, Ediția a 16-a, pp. 13-19. ISBN 978-172819080-8. DOI: https://doi.org/10.1109/ICCP51029.2020.9266187 |
| EXPORT metadate: Google Scholar Crossref CERIF DataCite Dublin Core |
| IEEE International Conference on Intelligent Computer Communication and Processing Ediția a 16-a, 2020 |
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Conferința "IEEE 16th International Conference on Intelligent Computer Communication and Processing" Cluj-Napoca, Romania, 3-5 septembrie 2020 | ||||||
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| DOI:https://doi.org/10.1109/ICCP51029.2020.9266187 | ||||||
| Pag. 13-19 | ||||||
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Fuzzy sets are used in different fields and determination of the membership functions is one of the most important issues in the design of fuzzy systems. The paper presents an approach to that problem to provide solutions in specific cases. In context, a technique for extracting knowledge from measurements data sets was developed that allows to retrieve human expertise and the construction of algorithms for decision-making systems. Initially, the method was developed to be used in data-based fuzzy modeling for the micro-wire casting plant control. |
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| Cuvinte-cheie data-driven modeling, fuzzy system, knowledge extraction, measurements data set, membership function |
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